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How Data Scientists Use Python For The Problem Solving Process In Data Science?
The prominence for Data Science has grown immensely over the last few years due to the rise in the usage of Big Data. The primary objective of Data Science is to focus on extracting meaningful insights from the Big Data by making use of various Data Analysis techniques. These insights become very crucial in taking marketing and business strategies that help the businesses to scale & grow.
Among the different programming languages used for Data Science, most of the survey results have revealed that Python is the most extensively used language which is followed by R & SQL. Aspirants who are curious to step into the profession of a Data Scientist are must to have intense skills in relation to coding with Python. If you are new to Python, learn Data Science along with Python & work on multiple capstone projects by joining for Analytics Path Data Science Training In Hyderabad program.
Now, let’s take a look at how Data Scientists make use of Python programming for the problem solving process in Data Science.
- Data Collection & Cleansing
Python is known for its innumerable libraries with the help of which Data Scientists can play with Big Data of any format. With the help of Python libraries like PyMySQL and BeautifulSoup, analysts can easily scrap data from the web. There are other libraries which support the data cleaning operations where missing data sets can be easily addressed.
- Data Exploration
Once the data is mined & prepared for the data exploratory process, Data Scientists would be defining the business questions which they need to address using this data. Then, by making use of Python libraries like NumPy and Pandas, analysts can easily explore the insights from the data.
Once the insights are extracted & explored, it is then processed to perform data modeling with AI & Machine Learning.
- Data Modeling
Python is having a number of libraries that support the Machine Learning data modeling tasks. Data Scientists make use of Python libraries like Numpy, SciPy & Scikit-learn to apply Machine Learning algorithms on the data.
- Data Visualization
Data Scientists then make use of Python libraries lie Matplotlib or Plotly to present the data insights in attractive visual formats.
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